Heqing Yi on Muck Rack

Heqing Yi

As seen in: BMC Cancer, Academic Radiology
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Articles

Machine learning-based differentiation of benign and malignant adrenal lesions using 18F-FDG PET/CT: a two-stage classification and SHAP interpretation study | BMC Cancer | Full Text

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By Yun Wang, Yuqi Su, Jing Li, Deying Xie, Zhuolin Liu, Chengyang Sun, Jingjing Zhang, Heqing Yi, Ye Yuan, Yuhuang Cai, Jaesik Jeong
| BMC Cancer
This study aimed to explore the feasibility and clinical utility of applying interpretable machine learning algorithms to classify adrenal lesions using quantitative features derived from 18 F-FDG PET/CT imaging and clinical variables. The research was structured into two major predictive tasks: first, the binary classification of adrenal lesions as benign or malignant; and second, the subclassification of malignant lesions into lung cancer metastases and lymphoma.
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